e-learning
Bulk RNA Deconvolution with MuSiC
Abstract
Bulk RNA-seq data contains a mixture of transcript signatures from several types of cells. We wish to deconvolve this mixture to obtain estimates of the proportions of cell types within the bulk sample. To do this, we can use single cell RNA-seq data as a reference for estimating the cell type proportions within the bulk data.
About This Material
This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.
Questions this will address
- How do we infer cell type proportions from bulk RNA-seq data?
- How are these cell types grouped together?
Learning Objectives
- Construct Bulk and scRNA Expression Set Objects
- Inspect these objects for various properties
- Measure the abundance of certain cell type cluster markers compared to others
Licence: Creative Commons Attribution 4.0 International
Keywords: Single Cell, transcriptomics
Target audience: Students
Resource type: e-learning
Version: 7
Status: Active
Prerequisites:
- An introduction to scRNA-seq data analysis
- Introduction to Galaxy Analyses
Learning objectives:
- Construct Bulk and scRNA Expression Set Objects
- Inspect these objects for various properties
- Measure the abundance of certain cell type cluster markers compared to others
Date modified: 2024-06-14
Date published: 2022-02-11
External resources:
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